Large Scale Pedestrian Multi-Simulation for a Decision Support Tool

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dc.contributor.authorKarmakharm, Twinen_US
dc.contributor.authorRichmond, Paulen_US
dc.contributor.editorHamish Carr and Silvester Czanneren_US
dc.date.accessioned2013-11-08T10:31:58Z
dc.date.available2013-11-08T10:31:58Z
dc.date.issued2012en_US
dc.description.abstractAbility to simulate pedestrian behaviour on a large scale is essential in identifying potential dangers in public spaces during an evacuation. Multiple designs must be tested with varying parameters and run multiple times to achieve statistical significance due to the model's stochastic nature. In this short paper, we describe our prototype decision support tool that enables concurrent simulation on GPU-enabled computers by merging them to increase efficiency and dispatching simulation jobs across multiple machines on the network. Preliminary results with our GPU-optimised model have been shown to run at faster than real-time simulation speeds.en_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-93-7en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG12/041-044en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.2.11 [ARTIFICIAL INTELLIGENCE]en_US
dc.subjectDistributed Artificial Intelligenceen_US
dc.subjectMultiagent systemsen_US
dc.titleLarge Scale Pedestrian Multi-Simulation for a Decision Support Toolen_US
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